5 papers
Region-Adaptive Generative Compression with Spatially Varying Diffusion Models
Lucas Relic, Roberto Azevedo, Yang Zhang +3
Generative image codecs aim to optimize perceptual quality, producing realistic and detailed reconstructions. However, they often overlook a key property of human vision: our tende…
UMAMI: Unifying Masked Autoregressive Models and Deterministic Rendering for View Synthesis
Thanh-Tung Le, Tuan Pham, Tung Nguyen +3
Novel view synthesis (NVS) seeks to render photorealistic, 3D-consistent images of a scene from unseen camera poses given only a sparse set of posed views. Existing deterministic n…
GeoDiff: Geometry-Guided Diffusion for Metric Depth Estimation
Tuan Pham, Thanh-Tung Le, Xiaohui Xie +1
We introduce a novel framework for metric depth estimation that enhances pretrained diffusion-based monocular depth estimation (DB-MDE) models with stereo vision guidance. While ex…
One Diffusion to Generate Them All
Duong H. Le, Tuan Pham, Sangho Lee +5
We introduce OneDiffusion, a versatile, large-scale diffusion model that seamlessly supports bidirectional image synthesis and understanding across diverse tasks. It enables condit…
Diffusion-Guided Gaussian Splatting for Large-Scale Unconstrained 3D Reconstruction and Novel View Synthesis
Niluthpol Chowdhury Mithun, Tuan Pham, Qiao Wang +6
Recent advancements in 3D Gaussian Splatting (3DGS) and Neural Radiance Fields (NeRF) have achieved impressive results in real-time 3D reconstruction and novel view synthesis. Howe…